Demo entry 6624157



Submitted by anonymous on Jun 13, 2017 at 21:10
Language: Python. Code size: 540 Bytes.

rf_tuned = RandomForestClassifier(n_estimators=10, max_features=10,
                                  max_depth=5, criterion='entropy',
                                  bootstrap=True, random_state=221), yb_train)
res_tuned = rf_tuned.predict(Xb_test)
print classification_report(yb_test, res_tuned)
print accuracy_score(yb_test, res_tuned)
cv = StratifiedShuffleSplit(n_splits=4, test_size=0.2, random_state=10)
learning_curve_model(Xb_train, yb_train, rf_tuned, cv, np.linspace(0.1, 1.0, 10))

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